code: def load_data(
      self,
      data_frame: DataFrame,
      categorical_fields: Optional[Union[str, List[str]]] = None,
      numerical_fields: Optional[Union[str, List[str]]] = None,
      target_field: Optional[str] = None,
      parameters: Dict[str, Any] = None,
  ):
      cat_vars, num_vars = self.preprocess(
          data_frame, categorical_fields, numerical_fields, parameters
      )
  
      if not self.predicting:
          targets = (
              data_frame[target_field].to_numpy().astype(np.float32)
          )
          return [
              {DataKeys.INPUT: (c, n), DataKeys.TARGET: t}
              for c, n, t in zip(cat_vars, num_vars, targets)
          ]
  
      return [
          {DataKeys.INPUT: (c, n)} for c, n in zip(cat_vars, num_vars)
      ]
  
file_path: lightning-flash/src/flash/tabular/regression/input.py
imports: from typing import Any, Dict, List, Optional, Union
  import numpy
  from flash.core.data.io.input import DataKeys
  from flash.core.data.utilities.loading import load_data_frame
  from flash.core.utilities.imports import _PANDAS_AVAILABLE
  from flash.tabular.input import TabularDataFrameInput
label_desc: Use image node_id 1 for calling the TabularRegressionDataFrameInput obj's underlying member method code with example usage: obj.load_data(data_frame, categorical_fields, numerical_fields, target_field, parameters) and returns: unknown, unknown